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Server Quality Checklist

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  • Latest release: v1.0.2

  • Disambiguation5/5

    Each tool addresses a distinct aspect: account status, gift creation, retrieval by ID, listing with filters, and occasion enumeration. No functional overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (check_account, create_gift, get_gift, list_gifts, list_occasions) with no deviations.

    Tool Count5/5

    Five tools cover the core workflow (check credits, list occasions, create, retrieve, list) without unnecessary additions. The count is well-scoped.

    Completeness4/5

    The tool set covers credit checking, creation, retrieval, and listing. Missing are update/delete/cancel operations, but these are not essential for the video gift creation domain.

  • Average 4.4/5 across 5 of 5 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 3 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It discloses that film_url is only returned once delivered and suggests polling, but lacks details on idempotency, error handling, or rate limits.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two sentences, front-loaded with action and result, no unnecessary words.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given one parameter, no annotations, and no output schema, the description sufficiently covers what the tool does and when to use it. Minor missing details on error scenarios.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100% with one parameter. The description adds value by specifying that the gift_id comes from create_gift, which is beyond the schema's basic description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the verb 'Fetch', the resource 'one gift by id', and the returned data 'status and film_url'. It distinguishes from siblings by mentioning its use after create_gift.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says to poll after create_gift with render=true, which provides clear context. However, it does not explicitly mention when not to use it or alternatives.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the burden. It discloses that the tool lists occasions and that the ID drives song and tone. It does not describe any side effects or special behaviors, but for a read-only list with zero parameters, this is adequate.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two sentences, concise and front-loaded with the main purpose. Every sentence adds value.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given zero parameters, no output schema, and no annotations, the description covers the essential purpose and usage context. It could optionally mention if the list is exhaustive or static, but it is complete enough for its simplicity.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has zero parameters, so schema description coverage is 100%. The description does not need to add parameter details; the baseline for no parameters is 4.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool lists supported occasions, provides examples, and explains the purpose of the occasion ID for creating gifts. It is distinct from sibling tools like list_gifts or create_gift.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies when to use it (before creating a gift to get the occasion ID) but does not explicitly state when not to use it or provide alternatives. The context is clear enough for an agent.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so description carries full burden. It discloses ordering and filtering but omits details on pagination behavior beyond schema-defined limit, or error handling for missing keys. Adequate for a simple read operation.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two sentences, no redundancy. Front-loaded with main action and ordering. Every sentence serves a purpose.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given tool simplicity (list with optional filter), no output schema needed. Description covers core behavior. Sibling tools are distinct, so no missing context.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema already describes both parameters (100% coverage). Description adds value by giving a concrete example for 'status' ('e.g. 'delivered'') and linking it to a use case ('find finished films'), enhancing semantic understanding.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states verb 'List', resource 'this key's gifts', and ordering 'newest first'. Distinguishes from siblings like 'get_gift' (single) and 'create_gift' (creation).

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Suggests using status filter for specific retrieval (e.g., 'find finished films'), implying context for use. Does not explicitly contrast with other tools but the sibling names provide enough differentiation.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so description carries full burden. It discloses that it returns status and balance (read operation), with no side effects implied. Adequate for a zero-parameter tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two sentences, front-loaded with purpose. No wasted words. Efficient and direct.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple tool with no parameters and no output schema, the description provides complete information: what it does and when to use it.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    No parameters, so schema coverage is 100% by default. Description adds context about what is returned, meeting baseline for zero parameters.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states it returns account status and prepaid credit balance, with specific verb 'Return' and resource 'account status and prepaid credit balance'. It distinguishes from sibling tools which are about gifts and occasions.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says 'Use before rendering to confirm there are enough credits', giving clear context for when to use. No when-not-to or alternatives, but sufficient for this simple read tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Despite no annotations, description discloses credit consumption, rendering time, and the need for consent. It also explains how to track delivery via polling or watching list_gifts.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Three concise sentences: purpose, behavioral details, critical consent requirement. No wasted words, front-loaded information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Covers main workflow and key constraints for a complex multi-parameter tool. Lacks explicit mention of return value or that photo_urls are required for rendering (though schema states it). Still quite comprehensive.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%, so baseline is 3. Description adds value by emphasizing the consent parameter's requirement and clarifying defaults (tier, style, render). Some parameter details are already in schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states the tool creates a personalized video gift from photos and an original song, with optional rendering. It uses a specific verb and resource, distinguishing it from siblings like get_gift and list_gifts.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicit guidance on when to render (and spend credit) vs create a draft, with the requirement of consent=true for rendering. Also directs to poll with get_gift or watch list_gifts for status updates.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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  • Evaluate tool definition quality.

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